Data mining in general is the computational process of discovering patterns in large data sets and can involve the fields of artificial intelligence, machine learning, statistics, and database systems. The typical goal of data mining is to extract information from a data set and transform it into an understandable structure for further use. Data mining tasks include the automatic or semi-automatic analysis of large quantities of data to extract previously unknown interesting patterns such as groups of data records (i.e., cluster analysis), unusual records (i.e., anomaly detection) and dependencies (i.e., association rule mining).
However, known data mining techniques typically require careful model-building and deep initial insight into data. The subsequent steps may include writing custom code and running complex computations, and an end result is produced that is frequently either obvious or wrong. At best, data mining typically requires expert input and guidance, and returns results that only experts can understand and analyze.